InSAR-derived seasonal subsidence reflects spatial soil moisture patterns in Arctic lowland permafrost regions

Abstract

The identification of spatial soil moisture patterns is of high importance for various applications in high-latitude permafrost regions but challenging with common remote sensing approaches due to high landscape heterogeneity. Seasonal thawing and freezing of near-surface soil lead to subsidence–heave cycles in the presence of ground ice, which exhibit magnitudes of typically less than 10 cm. Our investigations document higher Sentinel-1 InSAR (interferometric synthetic aperture radar) seasonal subsidence rates (calculated per thawing degree days – a measure of seasonal heating) for locations with higher near-surface soil moisture compared to drier ones. Based on this, we demonstrate that the relationship of thawing degree days and subsidence signals can be interpreted to assess spatial variations in soil moisture. A range of challenges, however, need to be addressed. We discuss the implications of using different sources of temperature data for deriving thawing degree days on the results. Atmospheric effects must be considered, as simple spatial filtering can suppress large-scale permafrost-related subsidence signals and lead to the underestimation of displacement values, making Generic Atmospheric Correction Online Service for InSAR (GACOS)-corrected results preferable for the tested sites. Seasonal subsidence rate retrieval which considers these aspects provides a valuable tool for distinguishing between wet and dry landscape features, which is relevant for permafrost degradation monitoring in Arctic lowland permafrost regions. Spatial resolution constraints, however, remain for smaller typical permafrost features which drive wet versus dry conditions such as high- and low-centred polygons.